We call for papers on the following topics: (1) explaining other types of ML models (e.g. random forest, kernel machines, k-means), (2) explanation for other ML tasks (e.g. segmentation, unsupervised learning, reinforcement learning), (3) explaining beyond heatmaps (structured explanations, Q/A and dialog systems, human-in-the-loop), (4) Explaining beyond explaining (e.g., improving ML models and algorithms, verifying ML, getting insights).

Submissions are required to stick to the ICML format. Papers are limited to 6 pages (excluding references) and will go through a review process. Submissions don't need to be anonymized. The workshop allows submissions of papers that are under review or have been recently published in a conference or a journal. Authors should state any overlapping published work at the time of submission. Accepted papers will be posted on the website (upon agreement), but the workshop will not have any official proceedings, so it is non-archival. A selection of accepted papers will be invited to be part of a special journal issue on "Extending Explainable AI Beyond Deep Models and Classifiers".